This thesis investigates maintenance management practices within a machine shop
environment, focusing on a case study of a manufacturer specializing in high-precision
telecommunications equipment. The central objective is to evaluate the effectiveness of the
company’s current maintenance strategies, particularly preventive and predictive maintenance
and to assess their impact on operational efficiency, equipment reliability, and cost control.
Through a detailed analysis of the existing maintenance system, combined with targeted
improvement initiatives, the study demonstrates that well-structured and strategically aligned
maintenance practices can significantly reduce unplanned downtime, extend asset lifespan, and
enhance key performance indicators such as Overall Equipment Effectiveness (OEE). The
research employs a mixed-method approach, incorporating performance data, internal process
evaluation, and qualitative insights to draw actionable conclusions.
The findings reveal that integrating modern technologies such as condition monitoring sensors
and computerized maintenance management systems (CMMS) along with data-driven
decision-making, not only improves technical outcomes but also strengthens cross-functional
collaboration and long-term organizational resilience. These insights are especially relevant for
manufacturers operating in precision-driven industries, where minor disruptions can translate
into significant quality and productivity losses.
Ultimately, the thesis underscores the strategic role of maintenance management in supporting
continuous improvement, digital transformation, and sustainable operational performance in
modern industrial settings.